Triple

T1294872
Position Surface form Disambiguated ID Type / Status
Subject George Kistiakowsky E27631 entity
Predicate placeOfBirth P1 FINISHED
Object Kiev E17733 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kiev | Statement: [George Kistiakowsky, placeOfBirth, Kiev]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiev
Context triple: [George Kistiakowsky, placeOfBirth, Kiev]
  • A. Kyiv chosen
    Kyiv is the capital and largest city of Ukraine, serving as its political, cultural, and economic center.
  • B. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • C. Dnipro
    Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
  • D. Chernihiv
    Chernihiv is a historic city in northern Ukraine known for its ancient churches, rich cultural heritage, and role as a regional administrative and memorial center.
  • E. Odesa
    Odesa is a major port city on the Black Sea in southern Ukraine, known for its historic architecture, multicultural heritage, and key economic and cultural role in the country.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a496d6682881909ba658f1c1e0e2b0 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0f4031481908f5e3a53d8a72929 completed March 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd4729af08190a6de5388dab69fee completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:51 p.m.